R ESEARCH ARTICLE

doi: 10.2306/scienceasia1513-1874.2020.079

Effect of SNPs in genes regulating cell cycle control,apoptosis and inflammation on lung cancersusceptibility of northern Thai populationRattanasak Wongkomoncheda,b, Bruce Rannalac, Phongtape Wiwatanadated, Somchareon Saetenge,Jatupol Kampuansaia,f,∗, Daoroong Kangwanponga

a Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200 Thailandb PhD Program in Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200 Thailandc UC Davis Genome Center, University of California Davis, CA 95616 USAd Department of Community Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200

Thailande Department of Surgery, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200 Thailandf Research Center in Bioresources for Agriculture, Industry and Medicine, Chiang Mai University, Chiang

Mai 50200 Thailand

∗Corresponding author, e-mail: Jatupol.K@cmu.ac.thReceived 18 Apr 2020Accepted 28 Sep 2020

ABSTRACT: Northern Thai population has experienced a high incidence of lung cancer and greater rates of mortalityover the past several decades. In this study, blood samples and personal information were collected from 91 non-smallcell lung cancer patients and 84 cancer-free healthy unrelated volunteers living in northern Thailand. Eight functionalSNPs, including cell cycle control (TP53 Pro72Arg, MDM2 T309G, CCND1 G723A, CDKN1A Ser31Arg), apoptosis (FASLGC-844T, FAS G-1378A) and inflammation (TGFB1 T-1347C, TGFB1 Pro10Leu) were genotyped by multiplex allele-specific polymerase chain reactions. Odds ratios (OR) with 95% confidence intervals (CI) were calculated using logisticregression after making adjustments for age, gender and the smoking status of all participating subjects. No significantassociation between a single SNP and lung cancer risk was observed. However, a combination of TGFB1-1347T and10Pro allele carriers indicated a significantly increased risk for lung cancer (OR = 2.90, 95% CI = 1.01–8.4, P = 0.049)relative to wild-type genotypes. Among the participants, who had kitchens inside their homes, -1347T allele carriershad significant increase in lung cancer risk (OR = 5.9, 95% CI = 1.32–26.5, P = 0.020) when compared to the TGFB1-1347 C/C genotype carriers. In conclusion, we have observed a significant association between TGFB1-1347T alleleand either TGFB1 10Pro allele or having kitchen inside the house on risk elevation of non-small cell lung cancer amongthe population of northern Thailand.

KEYWORDS: lung cancer, northern Thailand, genetic susceptibility

INTRODUCTION

Lung cancer has been the most common form ofdiagnosed cancer worldwide and has been associ-ated with the highest rates of global incidence andmortality according to the International Agency forResearch on Cancer (IARC) in a 2018 report [1].In Thailand, lung cancer ranked second in mortalityrate among Thai males, preceded by liver cancer in2015. Lung cancer has high incidence in the north(especially the three provinces: Chiang Mai, Lam-pang and Lamphun) while liver cancer is extremelyhigh in the north-east [2, 3]. Based on the mostrecent volume of the Cancer in Thailand, the annual

age-standardized incidence rates per 100 000 (forthe years 2013–2015) of lung cancer for males andfemales, respectively, were 32.1 and 21.6 in ChiangMai, 32.9 and 19.5 in Lampang and 37.9, and19.8 in Lamphun [3]. Most of these patients werefound to have an advanced stage of lung cancerthat was either diagnosed as regional or as distantmetastases. Non-small cell lung cancer was foundto be the most common type of lung cancer withadenocarcinoma representing more than half of thetotal number of incidences [3]. Notably, more than80% of the lung cancer patients died within oneyear after being diagnosed [4]. This evidence clearlysuggests that lung cancer is a major health issue for

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the population of northern Thailand.The etiology of lung cancer among the northern

Thai population has been associated with exposureto carcinogens stemming from personal habits, oc-cupations and the environment along with certaininherited genetic factors. In accordance with thehigh prevalence (34.2%) of daily smoking habitsamong those residing in the northern part of Thai-land from 1991 to 2007 [5], tobacco smoking hasbeen identified as the most significant risk factor forlung cancer in this region. Environmental factors,including residential radon [6], outdoor air pollu-tion originating from vegetative burning, seasonalbushfires, engine exhaust emissions [7, 8], and in-door air combustion from the burning of biomassfuels [9], also contributed to the accelerated devel-opment of lung cancer among the northern Thaipopulation. An increased risk of TP53 somaticmutations in lung tissues was found among indi-viduals who used pesticides, had kitchens insidetheir homes, or lived in concrete homes in com-parison with those who were not exposed to anyof these risk factors [10]. Recently, a significantassociation between a high level of indoor radonin the household and a short telomere length hasbeen observed [11]. Interestingly, a combination ofgenetic polymorphisms within five genes was foundto be involved with carcinogen metabolism and DNArepair, and has been significantly associated withan elevated risk of developing lung cancer amongnorthern Thai women [12].

Effects of genetic variations, especially withregard to single nucleotide polymorphisms (SNPs)on the susceptibility to lung cancer, were dependedon their location within the genes and the role ofproteins encoded from those genes. Previous studieshave reported that the SNPs found in genes regu-lating p53-mediatied cell cycle control (i.e. TP53Pro72Arg, MDM2 T309G, CCND1 G723A, CDKN1ASer31Arg) [13–15], apoptosis (i.e. FASLG C-844T,FAS G-1378A) [16] and inflammation (i.e. TGFB1T-1347C, TGFB1 Pro10Leu) [17] could affect indi-vidual lung cancer susceptibility in Asians. Com-binations of these SNPs were also found to be sig-nificantly related to an increased risk of develop-ing lung cancer in some studies [15, 16]. In theabsence of a smoking habit, several SNPs in thesegene groups were significantly associated with anelevated risk of developing lung adenocarcinomaamong female non-smokers, who were exposed tocertain environmental factors, including cookingoil fumes, fuel smoke and environmental tobaccosmoke [18, 19].

This study aimed to evaluate the associationbetween candidate SNPs in genes regulating cellcycle control, apoptosis and inflammation with therisk of developing lung cancer among the populationof northern Thailand. Subgroup analyses, involvingcombinations of two SNPs in the same gene groupand individuals exposed to each of the potentialenvironmental risk factors for lung cancer, were alsoperformed.

MATERIALS AND METHODS

Ethics statement

During the course of our research, we protected therights of the participants along with their identities.We confirmed that all experiments were performedin accordance with the relevant guidelines and reg-ulations established for the experimental protocolon human subjects, as has been approved by theResearch Ethics Committee 3, Faculty of Medicine,Chiang Mai University, Thailand (certificate of ap-proval No. 128/2008). Written informed consentwas obtained from all participants prior to conduct-ing interviews and collecting blood samples.

Studied population

We performed a case-control study involving a sam-ple population of 91 lung cancer patients and 84control subjects. All individuals were residents ofthe northern region of Thailand and were of Thaiethnicity.

Study cases were recruited from patients whohad been diagnosed with non-small cell lung cancer,i.e. adenocarcinoma, squamous cell carcinoma,large cell adenocarcinoma, and adenocarcinoma insitu, based on pathological and/or cytological re-ports. Neither chemotherapy nor irradiation hadbeen administered to the participants within sixmonths prior to the date of blood sample collection.The controls were healthy volunteers who had noprior history of any form of cancer. They wererecruited as the spouses of lung cancer patients ornon-blood-related volunteers who underwent rou-tine annual health check-ups or as those who camealong with the cancer patients at the time of theirvisit to the doctor.

All subjects were interviewed, using question-naires, to obtain personal information includingdetails of occupation, any history of lung disease,any history of invasive cancers among their first-degree relatives, their personal habits (i.e. tobaccosmoking, alcohol consumption, fermented tea leafor betel nut chewing), and any environmental ex-

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posure to known lung carcinogens at their placesof residence (i.e. home layout, location of kitchen,burning activities). ’Ever smokers’, defined as per-sons having smoked daily for a year or longer, and‘Never smokers’ defined as persons never havingsmoked regularly for a year or longer.

Peripheral blood samples of each participantwere collected by venipuncture at the median cu-bital vein using a 6 ml vacutainer coated with an-ticoagulant K2EDTA. All blood samples were pro-cessed to obtain cell lysates within 48 h after beingcollected.

DNA extraction and SNP genotyping

Total genomic DNA from peripheral blood leu-cocytes was extracted according to the stan-dard inorganic salting out protocol [20]. Geno-types of TP53 Pro72Arg (rs1042522) and CDKN1ASer31Arg (rs1801270) were investigated by poly-merase chain reaction (PCR) with confrontingtwo-pair primers (PCR-CTPP), as has been de-scribed by Hishida et al [21]. Genotypes of fiveSNPs, including MDM2 T309G (rs2279744), FASG-1378A (rs2234767), FASLG C-844T (rs763110),TGFB1 T-1347C (rs1800469), and TGFB1 Pro10Leu(rs1800470), were detected by tetra-primer ampli-fication refractory mutation system (T-ARMS-PCR),as has been previously described [15, 22, 23]. De-tailed information of the studied SNPs are describedin Table 1.

A new set of T-ARMS primers was designed andused for the genotyping of CCND1 G723A (rs9344)in this study, using the online web service primerdesign [24]. The T-ARMS primer sequences thatwere used are listed as follows: forward outerprimer, 5′ AGT TCA TTT CCA ATC CGC CCT CCATG3′; reverse inner primer, 5′ CTG CCT GGG ACATCA CCC TCA CTT CCT 3′; forward inner primer,5′ TCC TCT CCA GAG TGA TCA AGT GTG ACACG3′; reverse outer primer, 5′ GTT CTA GGA GCA GTGGAA GAA GCC GGTG 3′. Mismatches between thesecond bases from 3′ terminal of the inner primersand DNA templates were intentionally designed tofurther enhance specificity. The estimated sizes ofthree possible amplicons were 214 bp for CCND1723G allele 169 bp for CCND1 723A allele and317 bp for the control products of two outer primers.

The primers and PCR cycling conditions for eachSNP genotyping were modified from the relevantmanufacturers’ protocols according to the speci-fied primers and the size of the amplicons neededto achieve distinguishable allelic-specific products(Table S1). Standard PCR conditions were estab-

lished and initiated with an activation step (95 °Cfor 12 min), followed by amplification steps (30–40cycles of 94 °C for 20 s, 60–65 °C for 40 s, 72 °C for20–60 s), and completed with a final extension step(72 °C for 7 min) (Table S1).

The amplified products were subjected to elec-trophoresis in agarose gel. The percentage ofagarose gel was depended on the size differ-ences among the amplicons (Table S1). After elec-trophoresis, gels were stained with ethidium bro-mide and examined under Bio-Rad Gel Doc™ 2000Gel Documentation Systems using Quality One®program (Hercules, CA, USA). Amplified prod-ucts were compared with 100 bp DNA GeneRuler(Thermo Scientific, Ontario, Canada), and a geno-type of each sample was identified by comparingwith three positive controls that had been genotypedpreviously by direct sequencing.

Statistical analysis

All statistical analyses were performed using IBMSPSS Statistics version 27.0 (IBM Corp., NY, USA)following the specific instructions of the statisticalmethods established for health care research. Con-tinuous variables were transformed into categoricalvariables using appropriate cut-offs based on theacquired data. For descriptive data of the twosubject groups, chi-square tests were used to testfor the presence of any statistical differences at asignificance level of 0.05 (α = 0.05).

Any deviations from the Hardy-Weinberg equi-librium (HWE) of each SNP locus were assessedusing the chi-square goodness-of-fit test statistics.Odds ratios (OR) and a 95% confidence interval(CI) were used to evaluate the association betweenthe risk of acquiring lung cancer and the influencedimpact of an individual SNP or the combined effectsof two SNPs within the same gene group, or thecombined effects of the SNPs and any potentialenvironmental risk factor. Stratified analysis foreach environmental risk factor was done to de-termine any lung cancer risk among subjects thatwere more likely exposed to environmental lungcarcinogens (by having kitchens inside their homes,being exposed to burning activities and those livingin wooden houses). Using multivariable logisticregression, ORs were adjusted for age, gender andsmoking status in the overall analyses of individ-ual SNP genotypes and combinations of two SNPswithin the same gene group; while ORs were ad-justed for the smoking habits of the participantsduring the course of the subgroup analyses involvingany of the environmental risk factors.

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Table 1 General information of the studied SNPs.

Abbrev.a Gene namea dbSNP ID HGVS nomenclatureb Common name GMAFc

(Alternate name)

Cell cycle control genesTP53 Tumor protein p53 rs1042522 NM_ 000546.6:c.215C>G (p.Pro72Arg) Pro72Arg (Arg72Pro) 0.45707 (G)MDM2 MDM2 proto-oncogene rs2279744 NM_ 002392.5:c.14+309T>G T309G (SNP309) 0.36661 (G)CDKN1A Cyclin dependent kinase

inhibitor 1Ars1801270 NM_ 000389.5:c.93C>A (p.Ser31Arg) Ser31Arg 0.25619 (A)

CCND1 Cyclin D1 rs9344 NM_ 053056.2:c.723G>A (p.Pro241=) G723A (G870A) 0.41354 (A)

Apoptosis genesFASLG Fas ligand rs763110 NM_ 000639.2:c.-844C>T C-844T (T-844C) 0.46965 (C)FAS Fas cell surface death receptor rs2234767 NM_ 000043.5:c.-1378G>A G-1378A (G-1377A) 0.18411 (A)

Inflammation cytokine genesTGFB1 Transforming growth factor

beta 1rs1800469 NM_ 000660.6:c.-1347T>C T-1347C (C-509T) 0.36801 (T)

rs1800470 NM_ 000660.7:c.29C>T (p.Pro10Leu) Pro10Leu (Leu10Pro) 0.45467 (C)

a According to the HUGO Gene Nomenclature Committee at the European Bioinformatics Institute.b According to the recommendations of the Human Genome Variation Society (HGVS).c Global minor allele frequency (GMAF) in the ClinVar database.

Fig. 1 CCND1 G723A genotyping by T-ARMS-PCR tech-nique. Three possible genotype products are as follows;G/A (214-bp and 169-bp), G/G (214-bp) and A/A (169-bp). The internal control products are 317-bp amplicons.N: negative control, M: 100-bp DNA ladder.

RESULTS

The demographic characteristics of the patients andthe controls, together with their prevalence of ex-posure to the listed environmental lung cancer riskfactors, are shown in Table 2. The mean age of thepatients with ever smoking habits were higher thanthe healthy control group. Among the environmen-

tal factors, significant differences were observedbetween cancer patients and the control groups onlyin proportion to their smoking status (P < 0.01).

Individual SNP genotyping was successfullydone with either PCR-CTPP or T-ARMS-PCR. The es-tablishment of newly designed T-ARMS-PCR primersfor the genotyping of CCND1 G723A is shown inFig. 1. Using the gel electrophoresis technique,one of three possible genotypes of CCND1 G723Apolymorphism, including G/A (214-bp and 169-bp),G/G (214-bp) and A/A (169-bp), was identified foreach sample. SNP genotyping of the randomly se-lected samples was twice repeated meticulously, andall genotyping results were found to be consistent.

Using the chi-square goodness-of-fit test, wefound that the genotype distributions of all 8 se-lected SNP loci agreed with those of the HWE(P > 0.05) in both patients and controls. We thenused a dominant comparison model by combiningheterozygous and homozygous variants and usingthe homozygous wild type as a reference group.Multivariate logistic regression analyses (adjustedfor age, gender and smoking status) revealed thatno significant effects of any variant alleles wereobserved on the ORs of lung cancer risk at each SNP(Table 3).

We next examined the combined effects of twoSNPs within each group of genes regulating thepathway/process on lung cancer risk. According tothe ORs and 95% CIs (Table 4), individuals withboth -1347T and 10Pro alleles of TGFB1 had sig-nificantly increased their risk of developing lungcancer (OR = 2.90, 95% CI = 1.01–8.4, P = 0.049)in comparison with those that did not carry thesetwo alleles. No significant association was found

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Table 2 Characteristics of the studied population.

Variable Control group, n(%) Patient group, n(%) P value

Sample size N = 84 N = 91AgeMean±SD 52.5±9.11 62.2±9.37 <0.001(Minimum–Maximum) 26–77 40–84Gender 0.22Female 41 (48.8) 36 (38.7)Male 43 (51.2) 55 (61.3)

Histological type of lung cancerAdenocarcinoma (ADC) 58 (63.7)Squamous cell carcinoma (SQC) 25 (27.5)Large cell carcinoma (LAC) 5 (5.5)Adenocarcinoma in situ (AIS) 3 (3.3)

Smoking status <0.001Never 49 (58.3) 16 (17.6)Ever 35 (41.7) 75 (82.4)

Kitchen location 0.63Outside house 44 (52.4) 51 (56.0)Inside house 40 (47.6) 40 (44.0)

Housing materials 0.79Concrete house 33 (39.3) 34 (37.4)Wooden house 51 (60.7) 57 (62.6)

Burning activity 0.48Once a week or none 31 (36.9) 29 (31.9)Twice a week or more 53 (63.1) 62 (68.1)

Table 3 Effects of individual SNPs on the risk of being diagnosed with lung cancer. Odds ratio (OR) and 95% confidenceintervals (CI) were estimated using multivariate logistic regression model and were adjusted for age, gender andsmoking status.

SNPs Controls, n(%) Patients, n(%) OR (95% CI) P value

Cell cycle control genesTP53 Pro72Arg 83 91Arg/Arg 19 (22.9) 23 (25.3) 1.00 (reference)Arg/Pro + Pro/Pro 64 (77.1) 68 (74.7) 0.86 (0.376–1.95) 0.71MDM2 T309G 83 91T/T 16 (19.3) 20 (22.0) 1.00 (reference)T/G + G/G 67 (80.7) 71 (78.0) 0.75 (0.307–1.82) 0.52CDKN1A Ser31Arg 83 91Ser/Ser 22 (26.5) 28 (30.8) 1.00 (reference)Ser/Arg + Arg/Arg 61 (73.5) 63 (69.2) 1.23 (0.56–2.72) 0.61CCND1 G723A 80 90G/G 7 (8.8) 14 (15.6) 1.00 (reference)G/A + A/A 73 (91.2) 76 (84.4) 0.44 (0.138–1.43) 0.17

Apoptosis genesFASLG C-844T 81 90T/T 11 (13.6) 9 (10.0) 1.00 (reference)T/C + C/C 70 (86.4) 81 (90.0) 0.95 (0.320–2.79) 0.92FAS G-1378A 79 90G/G 24 (30.4) 31 (34.4) 1.00 (reference)G/A + A/A 55 (69.6) 59 (65.6) 0.93 (0.43–2.04) 0.86

Inflammatory cytokine genesTGFB1 T-1347C 73 88C/C 18 (24.7) 9 (10.2) 1.00 (reference)C/T + T/T 55 (75.3) 79 (89.8) 2.57 (0.90–7.4) 0.079TGFB1 Pro10Leu 80 90Leu/Leu 12 (15.0) 7 (7.8) 1.00 (reference)Leu/Pro + Pro/Pro 68 (85.0) 83 (92.2) 2.13 (0.67–6.8) 0.20

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Table 4 Combined effects of two SNPs on the risk of being diagnosed with lung cancer. Odds ratio (OR) and 95%confidence intervals (CI) were estimated using multivariate logistic regression model and were adjusted for age, genderand smoking status.

SNPs Controls, n(%) Patients, n(%) OR (95% CI) P value

Cell cycle control genesTP53 Pro72Arg & MDM2 T309G 83 91The others 32 (38.6) 37 (40.7) 1.00 (reference)Pro/- & G/- 51 (61.4) 54 (59.3) 0.83 (0.398–1.71) 0.61Ser31Arg 83 91The others 36 (43.4) 41 (45.1) 1.00 (reference)G/- & Arg/- 47 (56.6) 50 (54.9) 1.18 (0.57–2.43) 0.66TP53 Pro72Arg & CCND1 G723A 80 90The others 20 (25.0) 33 (36.7) 1.00 (reference)Pro/- & A/- 60 (75.0) 57 (63.3) 0.51 (0.228–1.13) 0.098MDM2 T309G & CDKN1A Ser31Arg 83 91The others 30 (36.1) 42 (46.2) 1.00 (reference)G/- & Arg/- 53 (63.9) 49 (53.8) 0.78 (0.375–1.61) 0.49MDM2 T309G & CCND1 G723A 80 90The others 22 (27.5) 32 (35.6) 1.00 (reference)G/- & A/- 58 (72.5) 58 (64.4) 0.51 (0.230–1.14) 0.10CDKN1A Ser31Arg & CCND1 G723A 80 90The others 26 (32.5) 39 (43.3) 1.00 (reference)Arg/- & A/- 54 (67.5) 51 (56.7) 0.72 (0.341–1.51) 0.38

Apoptosis genesFASLG C-844T & FAS G-1378A 79 90The others 33 (41.8) 34 (37.8) 1.00 (reference)C/- & A/- 46 (58.2) 56 (62.2) 1.10 (0.53–2.32) 0.80

Inflammatory cytokine genesTGFB1 T-1347C & TGFB1 Pro10Leu 72 88The others 18 (25.0) 9 (10.2) 1.00 (reference)T/- + Pro/- 54 (75.0) 79 (89.8) 2.90 (1.01–8.4) 0.049*

* P < 0.05.

Table 5 Effects of individual SNPs on the risk of being diagnosed with lung cancer among individuals having kitchensinside their homes. Odds ratio (OR) and 95% confidence intervals (CI) were estimated using multivariate logisticregression model and were adjusted for age, gender and smoking status.

SNPs Controls, n(%) Patients, n(%) OR (95% CI) P value

Cell cycle control genesTP53 Pro72Arg 40 40Arg/Arg 10 (25.0) 12 (30.0) 1.00 (reference)Arg/Pro + Pro/Pro 30 (75.0) 28 (70.0) 0.90 (0.285–2.85) 0.86MDM2 T309G 40 40T/T 11 (27.5) 9 (22.5) 1.00 (reference)T/G + G/G 29 (72.5) 31 (77.5) 1.25 (0.380–4.1) 0.71CDKN1A Ser31Arg 40 40Ser/Ser 9 (22.5) 10 (25.0) 1.00 (reference)Ser/Arg + Arg/Arg 31 (77.5) 30 (75.0) 1.03 (0.311–3.40) 0.96CCND1 G723A 39 39G/G 2 (5.1) 7 (17.9) 1.00 (reference)G/A +A/A 37 (94.9) 32 (82.1) 0.152 (0.023–1.03) 0.053

Apoptosis genesFASLG C-844T 38 39T/T 7 (18.4) 4 (10.3) 1.00 (reference)T/C + C/C 31 (81.6) 35 (89.7) 1.08 (0.250–4.7) 0.91FAS G-1378A 38 39G/G 13 (34.2) 11 (28.2) 1.00 (reference)G/A + A/A 25 (65.8) 28 (71.8) 1.52 (0.49–4.7) 0.47

Inflammatory cytokine genesTGFB1 T-1347C 32 38C/C 11 (34.4) 4 (10.5) 1.00 (reference)C/T + T/T 21 (65.6) 34 (89.5) 5.9 (1.32–26.5) 0.02*TGFB1 Pro10Leu 37 39Leu/Leu 7 (18.9) 4 (10.3) 1.00 (reference)Leu/Pro + Pro/Pro 30 (81.1) 35 (89.7) 2.43 (0.54–10.9) 0.25

* P < 0.05.

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Table 6 Effects of individual SNPs on the risk of being diagnosed with lung cancer among individuals living in woodenhouses. Odds ratio (OR) and 95% confidence intervals (CI) were estimated using multivariate logistic regression modeland were adjusted for age, gender and smoking status.

SNPs Controls, n(%) Patients, n(%) OR (95% CI) P value

Cell cycle control genesTP53 Pro72Arg 50 57Arg/Arg 9 (18.0) 12 (21.1) 1.00 (reference)Arg/Pro + Pro/Pro 41 (82.0) 45 (78.9) 1.18 (0.338–4.1) 0.80MDM2 T309G 50 57T/T 9 (18.0) 13 (22.8) 1.00 (reference)T/G + G/G 41 (82.0) 44 (77.2) 0.64 (0.189–2.15) 0.47CDKN1A Ser31Arg 50 57Ser/Ser 10 (20.0) 21 (36.8) 1.00 (reference)Ser/Arg + Arg/Arg 40 (80.0) 36 (63.2) 0.75 (0.247–2.26) 0.61CCND1 G723A 48 57G/G 5 (10.4) 3 (5.3) 1.00 (reference)G/A +A/A 43 (89.6) 54 (94.7) 3.13 (0.41–23.7) 0.27

Apoptosis genesFASLG C-844T 49 47T/T 10 (20.4) 7 (12.3) 1.00 (reference)T/C + C/C 39 (79.6) 40 (87.7) 1.37 (0.353–5.3) 0.65FAS G-1378A 48 57G/G 15 (31.2) 20 (35.1) 1.00 (reference)G/A + A/A 33 (68.8) 37 (64.9) 1.24 (0.43–3.58) 0.69

Inflammatory cytokine genesTGFB1 T-1347C 43 56C/C 12 (27.9) 5 (8.9) 1.00 (reference)C/T + T/T 31 (72.1) 51 (91.1) 4.2 (0.95–18.5) 0.058TGFB1 Pro10Leu 49 57Leu/Leu 7 (14.3) 4 (7.0) 1.00 (reference)Leu/Pro + Pro/Pro 42 (85.7) 53 (93.0) 4.1 (0.77–21.6) 0.099

Table 7 Effects of individual SNPs on the risk of being diagnosed with lung cancer among individuals exposed to burningactivities. Odds ratio (OR) and 95% confidence intervals (CI) were estimated using multivariate logistic regressionmodel and were adjusted for age, gender and smoking status.

SNPs Controls, n(%) Patients, n(%) OR (95% CI) P value

Cell cycle control genesTP53 Pro72Arg 53 62Arg/Arg 9 (17.0) 12 (19.4) 1.00 (reference)Arg/Pro + Pro/Pro 44 (83.0) 50 (80.6) 0.58 (0.180–1.87) 0.36MDM2 T309G 53 62T/T 11 (20.8) 16 (25.8) 1.00 (reference)T/G + G/G 42 (79.2) 46 (74.2) 0.58 (0.195–1.71) 0.32CDKN1A Ser31Arg 53 62Ser/Ser 16 (30.2) 16 (25.8) 1.00 (reference)Ser/Arg + Arg/Arg 37 (69.8) 46 (74.2) 1.94 (0.70–5.4) 0.21CCND1 G723A 51 61G/G 5 (9.8) 9 (14.8) 1.00 (reference)G/A +A/A 46 (90.2) 52 (85.2) 0.44 (0.100–1.96) 0.28

Apoptosis genesFASLG C-844T 51 61T/T 7 (13.7) 5 (8.2) 1.00 (reference)T/C + C/C 44 (86.3) 56 (91.8) 1.11 (0.266–4.6) 0.89FAS G-1378A 51 61G/G 16 (31.4) 20 (32.8) 1.00 (reference)G/A + A/A 35 (68.6) 41 (67.2) 1.07 (0.390–2.95) 0.89

Inflammatory cytokine genesTGFB1 T-1347C 46 59C/C 11 (23.9) 9 (15.3) 1.00 (reference)C/T + T/T 35 (76.1) 50 (84.7) 1.35 (0.397–4.6) 0.63TGFB1 Pro10Leu 51 61Leu/Leu 8 (15.7) 7 (11.5) 1.00 (reference)Leu/Pro + Pro/Pro 43 (84.3) 54 (88.5) 1.44 (0.384–5.4) 0.59

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between any other combination of two SNPs withinthe same gene groups and the risk of acquiring lungcancer.

Lung cancer susceptibility risks were evaluatedamong individuals who were exposed to each ofthe three environmental risk factors, including thosehaving kitchens inside their houses (Table 5), thoseliving in wooden houses (Table 6), and those ex-posed to burning activities in and around theirhomes (Table 7). Interestingly, a significant associ-ation was observed between a combined effect ofSNPs and the location of the kitchen for lung cancerrisk. Among participants who had kitchens insidetheir houses, TGFB1-1347T allele carriers were asso-ciated with a significant increase risk of lung cancer(OR= 5.9, 95% CI= 1.32–26.5, P= 0.020, adjustedfor age, gender and smoking status) in comparisonwith the TGFB1-1347 C/C genotype carriers. Albeitsomewhat non-significant, two SNPs in the TGFB1gene revealed potential associations with an ele-vated risk for developing lung cancer among thoseparticipants residing in wooden houses (P < 0.10)(Table 6). However, there was no significant asso-ciation observed between SNP and lung cancer riskamong those exposed to burning activities aroundtheir homes (Table 7).

DISCUSSION

In previous studies, the variant alleles of all eightstudied SNPs in this study had been reported toaffect changes in either protein functions or geneexpression and were found to be significantly as-sociated with lung cancer risk. However, effectsof these SNP variations and the potential environ-mental risk factors for susceptibility to lung canceramong the people of northern Thailand has not yetbeen evaluated. Although, there were no significantassociations between each of the studied SNPs anda risk for lung cancer in the multivariate analyses,a potential association between the TGFB1 T-1347Cpolymorphism and a risk of acquiring lung cancerwas observed. It was likely that individuals carrying-1347T alleles would have a 2-fold increased riskof developing lung cancer (Table 3). In a stratifiedanalysis of smoking history, Park et al [16] foundthat having at least one -1347T allele was associatedwith a 3.8-fold increased risk of acquiring lungcancer among heavy smokers (¾30 pack-years).Moreover, a 1.2-fold increased risk of acquiring lungcancer was found among Asian individuals whocarried at least one TGFB1-1347T allele in the meta-analysis [25]. However, a significant inverse asso-ciation was observed between the TGFB1 T-1347C

polymorphism and a lung cancer risk in several pre-vious studies conducted among Asian populations.Kang et al [25] found that the TGFB1 -1347T allelecarriers displayed 27% and 37% reduced risks ofacquiring lung cancer and lung adenocarcinoma,respectively. These results were obtained frommultivariate analyses after being adjusted for anypotential confounding factors, including age, gen-der, smoking status, and, especially, pack-years ofsmoking [26].

Although we observed a significant associationbetween a combination of the two SNPs in theTGFB1 gene, namely -1347T and 10Pro alleles,these two SNPs were found to be in strong link-age disequilibrium [17, 18]. Both TGFB1 T-1347Cand Pro10Leu are known to be functional polymor-phisms that affect the levels of TGFB1 transcriptionand TGF-β1 secretion [27]. However, there hasbeen no experimental evidence showing the effectof combining TGFB1 T-1347C and Pro10Leu poly-morphisms on the levels of TGF-β1 [28]. Basedon the functional studies of each SNP, it has beenhypothesized that synergy between TGFB1 upregu-lation (caused by -1347T allele) together with highlevels of TGF-β1 secretions (caused by 10Pro allele)might lead to a substantial increase in the plasmalevels of TGF-β1. Together with an inactivation ofkey mediators in TGF-β1 signaling (e.g. SMAD4),the role of TGF-β1 was switched from acting as atumor-suppressive, by inducing cell cycle arrest andapoptosis, to serving as a tumor-promoting factorvia immunosuppression by highly secreted TGF-β1proteins in the tumor microenvironment [29, 30].However, our observations of significant increasesin the risk of developing lung cancer among indi-viduals who carry both -1347T and 10Pro alleles ofTGFB1 were inconsistent with those of a previousstudy conducted upon the Korean population [26].Kang et al [26] found that the TGFB1 haplotype,with -1347T and 10Pro, was significantly associatedwith a 25% reduction in the risk of being diag-nosed with lung adenocarcinoma. However, neitheroverall lung cancer nor squamous cell carcinomasubtypes were related to the TGFB1 haplotype with-1347C and 10Leu after adjustments were madefor age, gender, smoking status, and pack-years ofsmoking.

We have observed a significant association be-tween the TGFB1-1347T allele and a risk of develop-ing lung cancer among individuals who had kitchensinside their houses. TGFB1-1347T allele carrierswere associated with about a 5-fold increased riskof being diagnosed with lung cancer in comparison

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ScienceAsia 46 (2020) 9

with the TGFB1-1347C allele carriers. Having akitchen inside the house was found to have signif-icantly contributed to a high prevalence (45.6%)of TP53 somatic mutations that were observed inlung cancer patients in comparison with lung can-cer patients who had kitchens outside their houses(16.7%) [10]. The severity of this factor with regardto an increased risk of lung cancer may dependupon certain characteristics or features of the sub-ject’s home, such as the number of windows, thepresence of a chimney, proper air ventilation, andany cooking activities that occur inside the kitchenthat involve fuel used for cooking [31]. Moreover,the use of biomass fuels for cooking was recentlyfound to be associated with long-term exposureto cancer-causing substances, including polycyclicaromatic hydrocarbons, such as benz[a]anthracene,benzo[k]fluoranthrene, benzo[a]pyrene, and theirnitro derivatives, that were found to have accumu-lated in the homes of lung cancer patients residingin Chiang Mai Province [9]. Undeniably, inhalationof these substances contributes to the developmentof lung cancer. On the other hand, the longer onespends inside their home, the greater the risk theyappear to have of developing lung cancer. Trans,trans-2,4-decadienal (tt-DDE or 2,4-De), a specifictype of dienaldehyde in cooking oil fumes was foundto be associated with increased cell proliferation andenhanced production of tumour necrosis factor-α(TNF-α) in human bronchial epithelial cells [32].This TNF-α in cooperation with TGF-β1, which isup-regulated by the -1347T allele, could promotecancer progression through epithelial-mesenchymaltransition (EMT) [29, 33]. Thus, individuals whohad kitchens inside their houses while carryingTGFB1-1347T alleles could have an increased riskof developing lung cancer.

At first, we expected that the participants whowere exposed to burning activities around theirhomes would have a greater likelihood of long-termexposure to airborne particulate matters that wouldsubsequently lead to lung cancer. Vegetative burn-ing was the main source of particulate matters, withan aerodynamic diameter of smaller than 10 µm(46–82% of the total PM10 concentration), duringthe period of June 2005 to June 2006 in Chiang Maiand Lamphun Provinces [8]. Burning in open fieldsis a convenient way to get rid of agricultural residuesafter harvesting crops. Smoke from bush fires inthis region and from surrounding countries duringthe dry season are brought here by southwesterlywinds that also contribute to the accumulation ofparticulate matters in the air of Chiang Rai Province,

the northern most province of Thailand [34, 35].For every 10-µg/m3 change in the exposure ofPM10, the risk of developing lung cancer and lungadenocarcinoma would increase by 9% and 29%,respectively [36]. However, we did not observe anysignificant association between each of the studiedSNPs and the risk of being diagnosed with lungcancer among participants who were exposed toburning activities around their homes. However,having or not having exposure to burning activitiesaround the home may depend upon a number ofother factors, such as the location of the house(urban or rural area), the weather, the crop seasons,and the amount of agricultural waste or householdwaste that is being produced by members of thathousehold. More detailed information about theexposure to burning activities may be useful indefining this parameter and in the application ofthe stratified analyses by a subgroup of the burningactivities.

Although we have observed some associationbetween the candidate SNPs in genes regulatingpathways/processes and a risk of developing lungcancer in the population of northern Thailand, wewere faced with some limitations during the courseof conducting this research. The limitations weresolely due to the small sample size. The limitednumber of samples in both patient and controlgroups affected the statistical power in the analysesof multivariate logistic regression, especially withregard to the stratified subject groups who were ex-posed to the designated environmental risk factors.Although the sample size of this study is acceptablefor multivariate logistic regression analyses (at leastten samples per one independent variable) [37],it was still less than the suggested level (at leasttwo controls per one case) [38], resulting in lowstatistical power. The expansion of the populationsize of the study by recruiting more lung cancerpatients and even more unrelated control subjectsfrom the same district may be beneficial for anincoming case-control study. With an adequatesample size, consideration of other risk factors forlung cancer, such as education level, occupation,exposure to second-hand smoke, previous experi-ence with lung diseases, the use of household solidfuels, and a family history of lung cancer, as well asmenstrual and reproductive factors in women, canbe evaluated for any association with lung cancerdevelopment in further studies.

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10 ScienceAsia 46 (2020)

CONCLUSION

In conclusion, we have observed significant associa-tions between TGFB1-1347T allele and either TGFB110Pro allele or having kitchen inside the housewith an elevated risk of non-small cell lung canceramong the population of northern Thailand. Ourresults suggest that there are mutual contributionsof individual genetic susceptibility and exposure toenvironmental carcinogens for the development oflung cancer in this region.

Appendix A. Supplementary data

Supplementary data associated with this arti-cle can be found at http://dx.doi.org/10.2306/scienceasia1513-1874.2020.079.

Acknowledgements: The authors wish to thank all ofthose who participated in this research project by pro-viding necessary information through the interview formsand by donating blood samples for the SNP genotypingprocess. This research project was jointly funded bythe Royal Golden Jubilee PhD Programme (grant no.PHD/0077/2550), the Thailand Science Research and In-novation and the National Research Council of Thailand.JK gratefully acknowledges the financial support providedby CMU Mid-Career Research Fellowship program, ChiangMai University, Thailand.

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ScienceAsia 46 (2020) S1A

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